Assessing disparities in real-world overall survival (rwOS) among sociodemographic groups in advanced ovarian cancer (aOC): The impact of biomarker testing and first-line (1L) maintenance therapies (mtx).
Notice bibliographique
Résumé
217 Background: Sociodemographic inequities in aOC survival have been documented and are thought to be largely the result of unequal access to guideline recommended care. In a previous phase of this study with a similar cohort of patients (pts), results showed lower rates of biomarker testing and use of 1L mtx in some socioeconomic status (SES) and racial groups. This study aims to evaluate the association between pts and clinical characteristics on rwOS in aOC. We also estimate how much of the association between race or SES and rwOS is due to biomarker testing and 1L mtx. Methods: An observational cohort study of US pts with newly diagnosed aOC was conducted between 1 Jan 2019 and 30 Dec 2023 using retrospective clinical data from the nationwide Flatiron Health electronic health record-derived deidentified database. Cox regression was used to assess associations between pts and clinical characteristics and rwOS from time of diagnosis, and between biomarker status and receipt of 1L mtx and rwOS. Mediation analysis was used to estimate indirect effects of differences in the probability of receiving recommended biomarker testing and 1L mtx (defined as pts who had known homologous recombination deficiency [HRD] or BRCA status and received a PARP inhibitor [PARPi] if BRCA mutation [BRCAm] or HRD-positive) on rwOS due to race (non-white vs white) and SES (1 [low] vs 2, 3, 4, 5 or unknown). Results: 1287 pts were included in the cohort; median age 68 years (range 22–85); 61% of pts were of white race and 39% non-white; 12% of pts SES 1, 15% SES 2, 21% SES 3, 22% SES 4, 23% SES 5, and 7% SES unknown. Eighty-eight percent of pts received BRCA testing and 49% HRD testing (including BRCAm); 30% (n = 392) received 1L PARPi mtx. Younger age, FIGO stage III, Eastern Cooperative Oncology Group 0, serous histology, and receipt of surgery were all associated with improved rwOS. Receipt of biomarker testing and 1L mtx also had a strong association with improved rwOS. In the mediation analysis, the indirect effect of race through receipt of biomarker testing and 1L mtx was statistically significant and accounted for most of the difference in rwOS between white and non-white pts (Table). Conclusions: Lower rates of BRCA and HRD testing and 1L mtx were associated with worse rwOS. Much of the association in disparities in rwOS by race or SES was due to differences in modifiable risk factors related to biomarker testing and treatment patterns. This suggests that mitigating these differences has the potential to improve outcomes in non-white and lower SES pts with aOC. Effect of race or SES on median rwOS (95% CI), months. Indirect effect via BT + 1L mtx Direct effect other than BT + 1L mtx Total Race non-white −1.7 (−3.6, −0.1) −0.8 (−8.1, 6.6) −2.5 (−9.6, 5.0) SES 1 (low) −1.5 (−3.6, 0.4) −2.0 (−11.3, 8.7) −3.4 (−12.8, 7.3) BT, biomarker testing.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».